In order to predict whether organisms will evolve resistance to new antibiotics or whether organisms in live vaccines will re-evolve virulence we need to predict evolutionary changes that are the consequence of defined selections for new or improved biological functions. The proposed project seeks to answer the questions "What information about a microorganism do we require in order to accurately predict which genes will mutate, and what mutations will occur, in order for that organism to evolve a new function in response to a specific selective pressure?" The model system will be the evolution of a Lac PTS/phospho-beta- galactosidase system for the catabolism of lactose in Escherichia coli. Two distinct functions are required: (1) an EIIlac for transport and phosphorylation of lactose and (2) a phospho-beta-galactosidase enzyme to cleave the phosphorylated lactose. There are five distinct gene systems, each of them for the catabolism of beta-glucoside sugars, that are good candidates to evolve the new lactose-specific functions. There are four different kinds of information that can be used to predict which genes, and which sites within those genes, will evolve: (1) functional comparison approach, (2) the sequence/phylogeny approach, (3) the biochemical approach. (4) the fitness measurement approach, (5) the in vitro sexual-PCR approach. First the data required to make predictions according to each of those approaches will be obtained for each of the four gene systems. It is likely that the EIIlac function and the phospho beta-galactosidase functions will evolve from different genes systems. Therefore strains that express each of the possible pairs of gene systems will be used to select spontaneous mutants that express the evolved Lac PTS/phospho-beta-galactosidase system. The resulting mutants will then be characterized to determine which kind of data most accurately predicted the eventual evolutionary outcome.